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Questions and Answers of Management And Artificial Intelligence

8. Modify arc consistency with domain splitting to return all of the models and not just one. Give the algorithm.
7. Which of the following methods can(a) determine that there is no model, if there is not one(b) find a model if one exists(c) find all models?The methods to consider are(a) arc consistency with
6. Consider a scheduling problem, where there are five activities to be scheduled in four time slots. Suppose we represent the activities by the variables A, B, C, D, and E, where the domain of each
5. Consider how stochastic local search can solve Exercise 3. You should use the “stochastic local search” AIspace.org applet or the book’s Python code to answer this question. Start with the
4. Consider the complexity for generalized arc consistency beyond the binary case considered in the text. Suppose there are n variables, c constraints, where each constraint involves k variables, and
3. Consider the crossword puzzles shown in Figure 4.15.The possible words for (a) are:ant, big, bus, car, has, book, buys, hold, lane, year, ginger, search, symbol, syntax.The available words for (b)
2. Suppose you have a relation v(N, W) that is true if there is a vowel (one of:a, e, i, o, u) as the N-th letter of word W. For example, v(2, cat) is true because there is a vowel (“a”) as the
1. Consider the crossword puzzle shown in Figure 4.14.You must find six three-letter words: three words read across (1-across, 4-across, 5-across)and three words read down (1-down, 2-down, 3-down).
13. The depth-first branch-and-bound of Figure 3.12 is like a depth-bounded search in that it only finds a solution if there is a solution with cost less than bound. Show how this can be combined
12. Give a statement of the optimality of A * that specifies a class of algorithms for which A * is optimal. Give the formal proof.
11. Consider the algorithm sketched in the counterexample of the box.(a) When can the algorithm stop? (Hint: it does not have to wait until the forward search finds a path to a goal.)(b) What data
10. Bidirectional search must be able to determine when the frontiers intersect. For each of the following pairs of searches specify how to determine when the frontiers intersect.(a) Breadth-first
9. The overhead for iterative deepening with b − 1 on the denominator is not a good approximation when b ≈ 1. Give a better estimate of the complexity of iterative deepening when b ≈ 1. (Hint:
8. How can depth-first branch-and-bound be modified to find a path with a cost that is not more than, say, 10% greater than the least-cost path. How does this algorithm compare to A * from the
7. What happens if the heuristic function is not admissible, but is still nonnegative? What can we say about the path found by A * if the heuristic function(a) is less than 1 + ϵ times the
6. The A * algorithm does not define what happens when multiple elements on the frontier have the same f-value. Compare the following tie-breaking conventions by first conjecturing which will work
5. Draw two different graphs, indicating start and goal nodes, for which forward search is better in one and backward search is better in the other.
4. This question investigates using graph searching to design video presentations. Suppose there exists a database of video segments, together with their length in seconds and the topics covered, set
3. Consider the problem of finding a path in the grid shown in Figure 3.14 from the position s to the position g. A piece can move on the grid horizontally or vertically, one square at a time. No
2. Which of the path-finding_ search procedures are fair in the sense that any element on the frontier will eventually be chosen? Consider this question for finite graphs without cycles, finite
1. Comment on the following quote: “One of the main goals of AI should be to build general heuristics applicable to any graph-searching problem.”
9. Suppose you have a new job and must build a controller for an intelligent robot. You tell your bosses that you just have to implement a command function and a state transition function. They are
8. Suppose the robot has a battery that must be charged at a particular wall socket before it runs out. How should the robot controller be modified to allow for battery recharging?
7. Change the controller so that the robot senses the environment to determine the coordinates of a location. Assume that the body can provide the coordinates of a named location.
6. The current controller visits the locations in the to_do list sequentially.(a) Change the controller so that it is opportunistic; when it selects the next location to visit, it selects the
5. If the current target location were to be moved, the middle layer of Example 2.5 travels to the original position of that target and does not try to go to the new position. Change the controller
4. Consider the “robot trap” in Figure 2.11.(a) This question is to explore why it is so tricky for a robot to get to location g. Explain what the current robot does. Suppose one was to implement
3. The obstacle avoidance implemented in Example 2.5 can easily get stuck.(a) Show an obstacle and a target for which the robot using the controller of Example 2.5 would not be able to get around
2. Consider the top level controller of Example 2.6(a) If the lower level reach the timeout without getting to the target position, what does the agent do?(b) The definition of the target position
1. The start of Section 2.3 argued that it was impossible to build a representation of a world independently of what the agent will do with it. This exercise lets you evaluate this argument.Choose a
5. Choose four pairs of dimensions that were not compared in Section 1.5.10. For each pair, give one commonsense example of where the dimensions interact.
4. For each of the Winograd schemas in Example 1.2, what knowledge is required to correctly answer the questions? Try to find a “cheap” method to find the answer, such as by comparing the number
3. Find out about two applications of AI (not classes of applications, but specific programs). For each application, write, at most, one typed page describing it. You should try to cover the
2. Give as many disciplines as you can whose aim is to study intelligent behavior of some sort. For each discipline, find out what aspect of behavior is investigated and what tools are used to study
1. For each of the following, give five reasons why:(a) A dog is more intelligent than a worm.(b) A human is more intelligent than a dog.(c) An organization is more intelligent than an individual
• Inductive logic programming can be used to learn relational models, even when the values of features are meaningless names.
• Event calculus allows for continuous and discrete time and axiomatizes what follows from the occurrence of events.
• Situation calculus represents time in terms of the action of an agent, using the init constant and the do function.
• Many of the representations in earlier chapters can be made relational.
• Relational representations are used when an agent requires models to be given or learned before it knows what individuals it will encounter.
Exercise 14.8 Represent the electrical domain of previous chapters in ICL, so that it will run in AILog. The representation should include the probabilistic dependencies of Example 6.11 (page 238)
Exercise 14.7 For the representation of addition in Example 14.20 (page 617), it was assumed that observed z-values would all be digits. Change the representation so that the observed values can be
Exercise 14.6 Give some concrete specialization operators that can be used for top-down inductive logic programming. They should be defined so that making progress can be evaluated myopically.
Exercise 14.5 Suppose that, in event calculus, there are two actions, Open and Close, and a relation opened that is initially, at time 0, false. Action Open makes opened true, and action Close makes
Exercise 14.4 In this question, you will investigate using event calculus for the robot delivery domain.(a) Represent the move action in the event calculus.(b) Represent each of the sequences of
Exercise 14.3 AILog performs depth-bounded search. You will notice that the processing time for the previous questions was slow, and we required a depth bound that was close to the actual depth bound
Exercise 14.2 In this question, you will add a more complicated paint action than in previous exercise.Suppose the object paint can(Color) denotes a can of paint of color Color.Add the action
Exercise 14.1 Add to the situation calculus example (also available from the course web page) the ability to paint an object. In particular, add the predicate color(Obj, Col, Sit)that is true if
Exercise 13.16 In this question, you will write a meta-interpreter for parametrized logic programs. These are logic programs that can use constants in arithmetic expressions. The values for the
Exercise 13.15 Build an iterative deepening abductive reasoning system to find minimal consistent sets of assumables to imply a goal. This can be based on the depth-bounded meta-interpreter of Figure
Exercise 13.14 Write a meta-interpreter for definite clauses that does iterative deepening search. Make sure that it only returns one answer for each proof and that the system says no whenever the
Exercise 13.13 Write a meta-interpreter that allows both how and why questions.In particular, it should allow the user to ask how questions about a goal that has been proved after a why question.
Exercise 13.12 Write a program that takes in a tree produced from the metainterpreter that builds proof trees as shown in Figure 13.13 (page 587) and lets someone traverse the tree using how
Exercise 13.11 Extend the ask-the-user meta-interpreter to have questions that ask for instances. You should be able to interpret declarations that say that a predicate is functional and respond
Exercise 13.10 Write a meta-interpreter that allows for asking the users yes-orno questions. Make sure it does not ask questions to which it already knows the answer.
Exercise 13.9 Write a meta-interpreter that can ask multiple sources for information.Suppose that each source is identified by a universal resource identifier (URI).Suppose you have the predicates•
Exercise 13.8 The program of Figure 13.16 (page 590) allows duplicate delayed goals.Write a version of dprove that returns minimal sets of delayed goals, in their simplest forms.
Exercise 13.7 Modify the depth-bound meta-interpreter of Figure 13.12(page 587) so that(a) the bound is on the total length of the proof, where the length is the total number of instances of
Exercise 13.6 For the following, explain how each is categorized by BFO:(a) your skin(b) the period at the end of the previous sentence(c) the excitement a child has before a vacation(d) the trip
Exercise 13.5 A luxury hotel has multiple rooms to rent, each of which is comfortable and has a view. The hotel must also have more than one restaurant. There must be menu items for vegetarians and
Exercise 13.4 Suppose a “beach resort” is a resort that is near a beach that the resort guests can use. The beach has to be near the sea or a lake, where swimming is permitted. A resort must have
Exercise 13.3 Write an ontology for the objects that often appear on your desk that may be useful for a robot that is meant to tidy your desk. Think of the categories that (a) the robot can perceive
Exercise 13.2 Sam has proposed that any n-ary relation P(X1,X2,X3, . . . ,Xn) can be reexpressed as n − 1 binary relations, namely, P1(X1,X2).P2(X2,X3).P3(X3,X4)....Pn−1(Xn−1,Xn).Explain to Sam
Exercise 13.1 The aim of this exercise is to explore multiple representations for the same domain.Tic-tac-toe is a game played on a 3 × 3 grid. Two players, X and O, alternately place their marks in
• A meta-interpreter can be used to build a light-weight implementation of a knowledge-based system that can be customized to fit the requirements of the representation language.
• The ability to explain reasoning and debug knowledge in terms of semantic content can improve the usability of a knowledge-based system.
• OWL ontologies are built from individuals, classes, and properties. A class is a set of real and potential individuals. A property links an individual to a data type or an individual.
• Ontologies are required for knowledge sharing.
• Individual-property-value triples form a flexible, universal representation for relations.
• The independent choice logic allows for the specification of probabilistic models before the individuals are known.
• Inductive logic programming can be used to learn relational models, even when the values of features are meaningless names.
• Event calculus allows for continuous and discrete time and axiomatizes what follows from the occurrence of events.
• Situation calculus represents time in terms of the action of an agent, using the init constant and the do function.
• Many of the representations in earlier chapters can be made relational.
• Relational representations are used when an agent requires models to be given or learned before it knows what individuals it will encounter.
Exercise 12.17 Construct a knowledge base and a dictionary [based on Figure 12.11 (page 531)] to answer geographical questions such as that given in Figure 1.2(page 8). For each query, either show
Exercise 12.16 In this question, you are to write a definite clause knowledge base for the design of custom video presentations.Assume that the video is annotated using the relation segment(SegId,
Exercise 12.15 The aim of this question is to get practice writing simple logic programs.(a) Write a relation remove(E, L, R) that is true if R is the resulting list of removing one instance of E
Exercise 12.14 Consider the following logic program:ap(emp, L, L).ap(c(H, T), L, c(H, R)) ←ap(T, L, R).adj(A, B, L) ←ap(F, c(A, c(B, E)), L).(a) Give a top-down derivation (including all
Exercise 12.13 Consider the following logic program:rd(cons(H, cons(H, T)), T).rd(cons(H, T), cons(H, R)) ←rd(T, R).Give a top-down derivation, showing all substitutions for the query ask
Exercise 12.12 Consider the following logic program:f (empty,X,X).f (cons(X, Y),W, Z) ←f (Y,W, cons(X, Z)).Give each top-down derivation, showing substitutions (as in Example 12.31) for the query
Exercise 12.11 List all of the ground atomic logical consequences of the following knowledge base:q(Y) ← s(Y, Z) ∧ r(Z).p(X) ← q(f (X)).s(f (a), b).s(f (b), b).s(c, b).r(b).
Exercise 12.10 For each of the following pairs of atoms, either give a most general unifier or explain why one does not exist:(a) p(X, Y,a, b,W)p(E,c, F,G, F)(b) p(X, Y, Y)p(E, E, F)(c) p(Y,a, b,
Exercise 12.9 Give a most general unifier of the following pairs of expressions:(a) p(f (X), g(g(b))) and p(Z, g(Y))(b) g(f (X), r(X), t) and g(W, r(Q),Q)(c) bar(val(X, bb), Z) and bar(P, P)
Exercise 12.8 What is the result of the following application of substitutions:(a) f (A,X, Y,X, Y){A/X, Z/b, Y/c}.(b) yes(F, L) ← append(F, c(L, nil), c(l, c(i, c(s, c(t, nil))))){F/c(l,X1),
Exercise 12.7 Consider the following knowledge base:has access(X, library) ← student(X).has access(X, library) ← faculty(X).has access(X, library) ← has access(Y, library) ∧ parent(Y,X).has
Exercise 12.6 In a manner similar to Example 12.21 (page 511), show derivations of the following queries:(a) ask two doors east(r107, R).(b) ask next door(R, r107).(c) ask west(R, r107).(d) ask
Exercise 12.5 In Example 12.21, we always selected the leftmost conjunct to resolve on. Is there a selection rule (a selection of which conjunct in the query to resolve against) that would have
Exercise 12.4 In Example 12.21 (page 511), the algorithm fortuitously chose imm west(r109, r111) as the clause to resolve against. What would have happened if another clause had been chosen? Show the
Exercise 12.3 Consider the following knowledge base:r(a).r(e).p(c).q(b).s(a, b).s(d, b).s(e, d).p(X) ← q(X) ∧ r(X).q(X) ← s(X, Y) ∧ q(Y).Show the set of ground atomic consequences derivable
Exercise 12.2 Consider the language that contains the constant symbolsa, b, and c; the predicate symbols p and q; and no function symbols. We have the following knowledge bases built from this
Exercise 12.1 Consider a domain with two individuals (✂and☎), two predicate symbols (p and q), and three constants (a,b, and c). The knowledge base KB is defined by p(X) ← q(X).q(a).(a) Give
• Clark’s completion can be used to define the semantics of negation as failure under the complete knowledge assumption.
• Equality between terms means that the terms denote the same individual.
• It is possible to use definite clauses to represent natural language grammars.
• Function symbols are used to denote a possibly infinite set of individuals described in terms of other individuals. Function symbols can be used to build data structures.
• Substitutions are used to make instances of atoms and rules. Unification makes atoms identical for use in proofs.
• Datalog is a logical language with constants, universally quantified variables, relations, and rules.
• In domains characterized by individuals and relations, constants denoting individuals and predicate symbols denoting relations can be reasoned with to determine what is true in the domain.
Exercise 11.12 In Example 11.14 (page 483), some of the features are perfectly correlated (e.g., F6 and F7). Does having such correlated features affect what functions can be represented? Does it

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